Search Results - (( java implementation path algorithm ) OR ( layer perception study algorithm ))
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Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer
Published 2017“…The development tools used in developing this project is NetBeans by using Java for the implementation of the coding. The methodology that used for developing this system is the Dijkstra’s algorithm. …”
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Thesis -
2
Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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3
Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment
Published 2021“…In this study, a fast iterative method known as Rotated Successive Over-Relaxation (RSOR) is introduced. The algorithm is implemented in a self-developed 2D Java tool, UAV Planner. …”
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Article -
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Smart appointment organizer for mobile application / Mohd Syafiq Adam
Published 2009“…The main component of this prototype is the use of Dijkstra algorithm to compute the shortest path from source of appointment to the 6 points of destinations within UiTM Shah Alam. …”
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5
An application of artificial neural network on short term load forecasting using back propagation algorithm / Elia Erwani Hassan
Published 1998“…The Back Propagation Algorithm, which consists of the multi-layered perception model, makes possible to train the ANN training pattems. …”
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6
IoT Soil Moisture Monitoring and Irrigation System Development
Published 2020“…At the same time, with a self-sufficient and self-organized irrigation system based on the water-control algorithm. The developed system covered the three layers in IoT architecture: perception layer, network layer and application layer. …”
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Proceeding -
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Forecasting The Growth of Manufacturing Industry in Malaysia Using Artificial Neural Network
Published 2006“…The effectiveness of ANN for predicting one criterion, Y form several predictors, X, is investigated. Comparative studies are examined between the result of the predictions from the ANN model trained with Multi-Layer Feed forward Perception, a Generalised Regressions Neural Network (GRNN) algorithm and the result obtained from traditional statistical approach.…”
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Evolutionary cost-cognizant regression test case prioritization for object-oriented programs
Published 2019“…Therefore, this study proposed a cost-cognizant TCP approach for object-oriented software that uses path-based integration testing to identify the possible execution path extracted from the Java System Dependence Graph (JSDG) model of the source code using forward slicing technique. …”
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Application of artificial neural network in discriminating the agarwood oil quality using significant chemical compounds / Mohd Hezri Fazalul Rahiman … [et al.]
Published 2014“…Data Processing - ANN Application ( Data pre-processing using Z-score, ANN design structure/architecture - parameter optimisation, training and testing the algorithm) Result & Discussion: ANN parameter optimisation - final error for learning rate, momentum rate and hidden layer size ANN final design parameter - Nodes in input layer: 7, Nodes in hidden layer size: 2, Output layer size: 1, learning rate: 0.9, Momentum rate: 0.7, Error goal: 0.01, Epochs: 100 ANN prediction: high accuracy for training and testing prediction (refer to the figure in poster) Patent & List of contributions: 1. …”
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Book Section -
10
Multivariate Time Series Forecasting Of Crude Palm Oil Price Using Machine Learning Techniques
Published 2017“…Experiments were conducted using multi-layer perception, support vector regression and Holt Winter exponential smoothing techniques.The results were assessed by using criteria of root mean square error (RMSE),means absolute error (MAE),means absolute percentage error (MAPE) and Direction of accuracy (DA).Among these three techniques, support vector regression(SVR) with Sequential minimal optimization (SMO) algorithm showed relatively better results compared to multi-layer perceptron and Holt Winters exponential smoothing method. …”
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Article -
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Artificial neural network modeling of grinding of ductile cast iron using water based sio2 nanocoolant
Published 2014“…An artificial neural network model is developed for predicting the surface roughness and MRR. Multi-layer perception and a batch back propagation algorithm are used. …”
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Article -
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Cyber-Crime Detection: Experimental Techniques Comparison Analysis
Published 2023“…The objective of this research paper is to conduct experimental techniques comparison analysis for cyber-crime detection by reviewing all possible machine learning algorithms for automatic detection. The key focus of the study is on the use of eight classifiers models which are Logistic Regression (LR), Decision Tree (DT), K-nearest Neighbors (KNN), Support Vector Machine (SVM), Naive Bayes (NB), Random Forest (RF), eXtreme Gradient Boosting (XGBoost) and Multiple layer perception (MLP). …”
Conference Paper -
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Optimization of abrasive machining of ductile cast iron using water based SiO2 nanocoolant : a radial basis function
Published 2012“…Artificial neural network (ANN) model is developed for predicting the results of the surface roughness and MRR. Multi-Layer Perception (MLP) along with batch back propagation algorithm are used. …”
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Undergraduates Project Papers -
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